halcon_ext op• Data kinds: region → region
• Call: fullseye.apply(img, "hx_split_skeleton_region", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: split_skeleton_region (the HALCON reference is a useful guide to its meaning and parameters)
*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*
*Knob a does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
Stages (the ops that come before → this op, left to right):
▸ hx_split_skeleton_region: stages (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ hx_split_skeleton_region: other inputs (docs site)
Split a one-pixel-wide skeleton at its branch points: remove the junctions (>=3 neighbours) and take the connected components.
For each skeleton pixel of v > 0.5, counts the number of skeleton pixels nb in its 8-neighbourhood and returns a 0/1 float array with the pixels where nb >= 3 (branch points) removed. Removing the branch points splits the skeleton into connected components, one per branch.
• a, b are unused.
It assumes a 1-pixel-wide skeleton (the output of skeleton). If you pass thick lines or blobs, all interior pixels have nb >= 3 and almost everything disappears. The branch points themselves are not included in the output (if you need the branch positions, use junctions_skeleton). To handle the separated branches individually, apply hx_region_to_label downstream. Pixels adjacent to branch points are not removed, so at thick crossings where many directions meet, a 1-pixel remnant may remain still connected. A related op is r2_split_skeleton_lines.
Border handling: treat everything outside the image as background (0) (measured; tools/impl2/border_probe.py).
• gallery2d_halcon_ext family guide
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.
threshold 0.50 0.50 hx_split_skeleton_region 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_halcon_ext — py -3.11 examples/gallery2d_halcon_ext.py
• poc_fresco_craquelure — py -3.11 examples/poc_fresco_craquelure.py
region as input)identity · reg_erode · reg_dilate · reg_open · reg_close · fill_holes · select_largest · remove_small
halcon_ext)hx_gen_circle · hx_gen_ellipse · hx_gen_rectangle2 · hx_gen_checker_region · hx_gen_grid_region · hx_gabor · hx_fit_surface1 · hx_fit_surface2
*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.